Biomechanical Constraint

Biomechanical constraint in scientific modeling aims to incorporate realistic physical limitations and anatomical structures into computational models, improving accuracy and realism. Current research focuses on integrating these constraints into diverse applications, including medical image analysis (using physics-informed neural networks and anatomical priors), human pose estimation (leveraging musculoskeletal models and inverse kinematics), and neural network design (incorporating biological principles like Dale's Law and energy efficiency). This approach enhances the accuracy and interpretability of models across various fields, leading to improved diagnostic tools, more realistic simulations, and a deeper understanding of biological systems.